We aim to establish TensorFlow as a common platform for expressing various machine learning ideas, ensuring it can be used for deep learning, perception problems, and language understanding.

We conduct long-term research independent of any particular application and build open-source systems to assist with our research and deployment of machine learning models, like TensorFlow.

TensorFlow is increasingly being used in machine learning classes at top universities, illustrating core concepts in the curriculum.

The growth in interest for TensorFlow has led to nearly a thousand non-Google contributors globally, enhancing the system through feature additions and bug fixes.

The TPU program was initiated to meet the demand for high compute power for inference and training in AI applications.

Google Cloud will offer a virtual machine with a 180 teraflop TPU version 2 device, running TensorFlow programs quickly.

The open-source philosophy behind Llama and PyTorch aims to foster an ecosystem where every company can create their own AI, enhancing innovation across industries.

At Scale, we power the data infrastructure for the entire AI industry, with every major large language model built on top of our data engine, and we partner with enterprises and governments to implement this technology for their unique challenges.

We made these chips programmable via TensorFlow, allowing models to run on CPUs, GPUs, or TPUs with minimal modifications.